{"id":2123777,"url":"https://alion.io/job/upvanta-senior-data-engineer-spark-developer","title":"Senior Data Engineer / Spark Developer","company":{"id":1332,"name":"Upvanta","domain":"upvanta.com","url":"https://alion.io/company/upvanta-sp-z-o-o","size_band":"51-200","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"contractor","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Wrocław, Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":56000,"max_usd":92000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":107},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"CI/CD","optional":false},{"name":"Confluence","optional":false},{"name":"Docker","optional":false},{"name":"Grafana","optional":false},{"name":"Jenkins","optional":false},{"name":"Jira","optional":false},{"name":"Kanban","optional":false},{"name":"Kubernetes","optional":false},{"name":"Prometheus","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scrum","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Apache Hudi","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Delta Lake","optional":true},{"name":"Dynatrace","optional":true},{"name":"GCP","optional":true},{"name":"OpenTelemetry","optional":true}],"status":"live","first_seen_at":"2026-10-08T11:05:10Z","employer_posted_date":null,"last_verified_at":"2026-10-08T11:05:10Z","board_verified":false,"closed_at":null,"days_open":8,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":8},"description":"O projekcie\nDo zespołu Data Platform poszukujemy doświadczonego Spark / Data Lakehouse Developera, który będzie odpowiedzialny za projektowanie i rozwój rozwiązań do przetwarzania, synchronizacji oraz rekoncyliacji danych w środowisku Big Data. Osoba na tym stanowisku będzie współtworzyć nowoczesną architekturę Data Lakehouse opartą o Apache Spark, MongoDB oraz Apache Iceberg, dbając o jakość, wydajność i niezawodność procesów danych.\nZakres obowiązków\nProjektowanie i implementacja procesów rekoncyliacji danych w Apache Spark (PySpark, Spark SQL).\n\nPorównywanie danych pomiędzy warstwą ODS (MongoDB) a systemami źródłowymi oraz identyfikowanie rozbieżności.\n\nTworzenie i rozwój reguł jakości danych, wykrywanie braków, duplikatów oraz anomalii.\n\nBudowa i utrzymanie warstw Data Lakehouse w modelu Raw / Bronze / Silver / Gold.\n\nPraca z Apache Iceberg i zarządzanie wersjonowanymi zbiorami danych.\n\nOptymalizacja wydajności procesów Spark oraz kosztów przetwarzania danych.\n\nTworzenie i rozwijanie pipeline'ów CI/CD dla aplikacji Spark.\n\nImplementacja monitoringu, metryk i alertowania dla procesów danych.\n\nAutomatyzacja wdrożeń z wykorzystaniem Docker, Kubernetes oraz Spark Operator.\n\nAnaliza i rozwiązywanie problemów związanych z jakością, spójnością i dostępnością danych.\n\nTworzenie dokumentacji technicznej, diagramów architektury oraz runbooków.\n\nWspółpraca z Data Engineerami, DevOps Engineerami, Analitykami Biznesowymi i zespołami produktowymi.\n\nUdział w code review oraz mentoring mniej doświadczonych członków zespołu.\n\nWymagania\nMinimum 4 lata doświadczenia komercyjnego w pracy z Apache Spark.\n\nBardzo dobra znajomość PySpark, Spark SQL, DataFrame API oraz Structured Streaming.\n\nDoświadczenie w integracji Apache Spark z MongoDB przy wykorzystaniu MongoDB Spark Connector.\n\nPraktyczna znajomość Apache Iceberg oraz zarządzania wersjonowanymi tabelami danych.\n\nDoświadczenie w budowie rozwiązań Data Lake lub Data Lakehouse.\n\nDobra znajomość języka Python.\n\nDoświadczenie z Jenkins oraz budową pipeline'ów CI/CD.\n\nZnajomość narzędzi monitoringu i observability, w szczególności Prometheus oraz Grafana.\n\nDoświadczenie w pracy zgodnie z metodykami Agile (Scrum lub Kanban).\n\nPraktyczna znajomość Jira i Confluence.\n\nGotowość do pracy z biura 1-2 dni w tygodniu (Wrocław)\n\nMile widziane\nDoświadczenie z Delta Lake lub Apache Hudi.\n\nZnajomość Kubernetes, Docker oraz Spark Operator.\n\nDoświadczenie w pracy z rozwiązaniami OpenTelemetry lub Dynatrace.\n\nZnajomość zagadnień Data Quality, Data Governance oraz Data Observability.\n\nDoświadczenie w środowiskach chmurowych (Azure, AWS, GCP).\n\nTech stack\nStructured Streaming\nDataFrame API\nSpark SQL\nPySpark\nApache Spark\nPython\nData Lake\nApache Iceberg\nJenkins\nCI/CD","description_format":"text","description_chars":2728,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Custom Software Development","IT Staffing & Staff 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